许多工业产品表面纹理都可以被认为是由基本纹理单元在空间按照一定的规则进行排列组合的结果，但由于各种原因，这些有规则纹理图象经常出现的一些缺陷，因而检测这些有规则纹理图象的缺陷是机器视觉检测的重要内容，为了对这种缺陷进行有效地检测，在对这类纹理图象进行功率谱分析的基础上，根据人眼的视觉原理，设计了两类匹配Gabor滤波器，即正常纹理匹配Gabor滤波器和缺陷纹理匹配Gabor滤波器，前者能够突出正常纹理，抑制缺陷纹理，而后者恰恰相反，在将这两类滤波器用于规则纹理图象缺陷的自动检测时，均获得了良好的检测精度和速度。

The surfaces of many industrial products are formed from the textural primitives by placement rules on the image field. It is an important task of automatic vision inspection to detect the defects in these regular textures. In the paper, two types of matched Gabor filters, that is normal texture matched Gabor filters and defect matched Gabor filters, are designed based on power spectrum of the regular normal texture and the abnormal texture. The normal texture matched Gabor filters, whose band pass area is positioned on the dominant frequency components of the normal texture, are designed to uplift the normal texture while suppress the defect texture. On the other hand, the defect matched Gabor filters, the band pass area of which guarantees the predominance of frequency components of the defect texture, have the effects of uplifting the defect texture while suppressing the normal texture. Taking advantage of the recent progress of study on principle of human vision, a novel adaptive filter design method is presented. Experiments on edge enhancement for defect detection using these matched Gabor filters have yielded satisfactory results, as far as both the precision and the speed are concerned.